Uniform approximation of the Cox-Ingersoll-Ross process

DOI10.1239/aap/1449859803zbMath1335.65011arXiv1312.0876OpenAlexW2183134743MaRDI QIDQ2786430

Grigori N. Milstein, John G. M. Schoenmakers

Publication date: 12 February 2016

Published in: Advances in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.0876

zbMATH Keywords

algorithmstochastic differential equationconvergencenumerical examplesBrownian motionBessel functionconfluent hypergeometric equationCox-Ingersoll-Ross processDoss-Sussmann formalism

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Brownian motion (60J65) Ordinary differential equations and systems with randomness (34F05) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Bessel and Airy functions, cylinder functions, ({}_0F_1) (33C10) Confluent hypergeometric functions, Whittaker functions, ({}_1F_1) (33C15)

Related Items (4)

Strong convergence rates for Cox-Ingersoll-Ross processes -- full parameter range ⋮ Two methods of estimation of the drift parameters of the Cox–Ingersoll–Ross process: Continuous observations ⋮ High Order Splitting Methods for SDEs Satisfying a Commutativity Condition ⋮ On arbitrarily slow convergence rates for strong numerical approximations of Cox-Ingersoll-Ross processes and squared Bessel processes

Cites Work

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